@inbook{ffad9ea7c1074b7f96017877deb7b17f,
title = "Load balancing in heterogeneous networks using an evolutionary algorithm",
abstract = "Grammatical Evolution (GE) is applied to the problem of load balancing in heterogeneous cellular network deployments (HetNets). HetNets are multi-tiered cellular networks for which load balancing is a scalable means to maximise network capacity, assuming similar traffic from all users. This paper describes a proof of concept study in which GE is used in a genetic algorithm-like way to evolve constants which represent cell power and selection bias in order to achieve load balancing in HetNets. A fitness metric is derived to achieve load balancing both locally in sectors and globally across tiers. Initial results show promise for GE as a heuristic for load balancing. This finding motivates a more sophisticated grammar to bring enhanced Inter-Cell Interference Coordination optimisation into an evolutionary framework.",
author = "Michael Fenton and David Lynch and Stepan Kucera and Holger Claussen and Michael O'Neill",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Congress on Evolutionary Computation, CEC 2015 ; Conference date: 25-05-2015 Through 28-05-2015",
year = "2015",
month = sep,
day = "10",
doi = "10.1109/CEC.2015.7256876",
language = "English",
series = "2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "70--76",
booktitle = "2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings",
address = "United States",
}